Due to continued technological advancements in data storage systems and information processing systems, health care providers and organizations continue to migrate toward environments where most aspects of patient care management are automated, making it easier to collect and analyze patient information. Consequently, health care providers and organizations, etc., tend to accumulate vast stores of patient information, such as financial and clinical information, in electronic patient medical records in electronic databases. Health care organizations, however, typically maintain clinical information in a myriad of unstructured and structured formats, which may contain missing, incorrect, and inconsistent data.
One source of error or inconsistency for patient data stored in a database is due to the improper codification or classification of particular medical diagnoses and procedures in the form of standardized “Codes”. Various types of standardized coding systems have been developed as nationally accepted common formats for numerically specifying, e.g., medical conditions/diagnoses or medical services/resources. For instance, clinical data may be classified according to specific cases or medical conditions (or a group of diagnoses and conditions) using codes that follow the International Classification of Diseases (ICD) standard. In particular, ICD Codes include, for example, the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), which is based on the World Health Organization's Ninth Revision, International Classification of Diseases (ICD-9). ICD-9-CM is an official system of assigning codes to diagnosis and procedures associated with hospital utilization in the United States. The Tenth Revision (ICD-10) has been released, which is expected to be implemented soon. Other types of standardized coding systems include, for example, CPT (current procedural terminology) codes, HCPCS (health care procedure coding system) codes, DRG (diagnosis related group) codes and APC codes.
There are various factors that can contribute to the improper classification of patient clinical information using standardized Codes. For instance, the coding process can be viewed as a two-step mental process that includes (i) assessing/diagnosing a medical condition/disease based on, e.g., a patient's symptoms and (ii) assigning a Code (e.g., ICD code) to the medical condition/disease. Accordingly, the coding process is subjective to some extent, since the codification process can be performed by a variety of people who possess different skills and expertise, which can result in different assessments of a medical condition and/or codification of such assessments. For example, different doctors (e.g., surgeon, internist) may select different ICD codes to specify a diagnosis of a particular medical condition of a patient based on, the actual condition of a particular organ of the patient, or the symptomatic status of the patient.
Moreover, for some conditions, the coding system may not have sufficient data options to accurately reflect the condition. In addition, codes can be incorrectly input in electronic medical records of a patient as a result of human error. As a result, the diagnosis codes that are included in electronic patient medical records of a clinical database can inaccurately represent the actual medical condition of the patients.
The “Codes” that are included in patient medical records for classifying medical conditions and procedures can be used for various purposes, such as sources of information for clinical data analysis, as well as sources of data for electronic systems for insurance claims and medical billing. Therefore, it is important to properly codify medical conditions and services so that medical billings and insurance claim analyses will accurately reflect the actual medical conditions of the patient and medical services rendered. Indeed, inaccurate code assignments for medical conditions and services can result in inappropriate reimbursement for medical claims by insurance companies, as well as rejection or partial payment of medical claims.